{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "U0ukYqqzateL"
   },
   "source": [
    "## Setup (Colab)\n",
    "\n",
    "If in colab, you will need to install these dependencies, download this data, and the model weights. If you are not in colab, you may have some of these already installed, or may need to install other dependencies (e.g. pytorch).\n",
    "\n",
    "At the moment, every block in this section is commented out. Uncomment in order to run in colab and install/download."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "IiB2IaU6QyF9"
   },
   "source": [
    "### Install dependencies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "I2MLDXLJQmnB",
    "outputId": "55c703a5-4cb4-40fa-ccd7-0edc137db259"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting biopython\n",
      "  Downloading biopython-1.79-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl (2.3 MB)\n",
      "\u001b[K     |████████████████████████████████| 2.3 MB 5.3 MB/s \n",
      "\u001b[?25hCollecting biotite\n",
      "  Downloading biotite-0.32.0.tar.gz (31.8 MB)\n",
      "\u001b[K     |████████████████████████████████| 31.8 MB 1.8 MB/s \n",
      "\u001b[?25h  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
      "  Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
      "    Preparing wheel metadata ... \u001b[?25l\u001b[?25hdone\n",
      "Collecting fair-esm\n",
      "  Downloading fair_esm-0.4.2-py3-none-any.whl (39 kB)\n",
      "Requirement already satisfied: numpy in /usr/local/lib/python3.7/dist-packages (from biopython) (1.21.5)\n",
      "Requirement already satisfied: requests>=2.12 in /usr/local/lib/python3.7/dist-packages (from biotite) (2.23.0)\n",
      "Requirement already satisfied: networkx>=2.0 in /usr/local/lib/python3.7/dist-packages (from biotite) (2.6.3)\n",
      "Requirement already satisfied: msgpack>=0.5.6 in /usr/local/lib/python3.7/dist-packages (from biotite) (1.0.3)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests>=2.12->biotite) (2021.10.8)\n",
      "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests>=2.12->biotite) (3.0.4)\n",
      "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests>=2.12->biotite) (1.24.3)\n",
      "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests>=2.12->biotite) (2.10)\n",
      "Building wheels for collected packages: biotite\n",
      "  Building wheel for biotite (PEP 517) ... \u001b[?25l\u001b[?25hdone\n",
      "  Created wheel for biotite: filename=biotite-0.32.0-cp37-cp37m-linux_x86_64.whl size=38716237 sha256=4f117bb362fb5b23d42ab3d789bb99270e8e4dbd70bfc080aafe0c3b6d183cba\n",
      "  Stored in directory: /root/.cache/pip/wheels/46/9e/15/da04a4aae9330b947f032301925e5a2f1f6c27f673d39293f6\n",
      "Successfully built biotite\n",
      "Installing collected packages: fair-esm, biotite, biopython\n",
      "Successfully installed biopython-1.79 biotite-0.32.0 fair-esm-0.4.2\n",
      "Reading package lists... Done\n",
      "Building dependency tree       \n",
      "Reading state information... Done\n",
      "The following additional packages will be installed:\n",
      "  libc-ares2\n",
      "The following NEW packages will be installed:\n",
      "  aria2 libc-ares2\n",
      "0 upgraded, 2 newly installed, 0 to remove and 39 not upgraded.\n",
      "Need to get 1,274 kB of archives.\n",
      "After this operation, 4,912 kB of additional disk space will be used.\n",
      "Get:1 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libc-ares2 amd64 1.14.0-1ubuntu0.1 [37.5 kB]\n",
      "Get:2 http://archive.ubuntu.com/ubuntu bionic/universe amd64 aria2 amd64 1.33.1-1 [1,236 kB]\n",
      "Fetched 1,274 kB in 0s (3,480 kB/s)\n",
      "Selecting previously unselected package libc-ares2:amd64.\n",
      "(Reading database ... 155455 files and directories currently installed.)\n",
      "Preparing to unpack .../libc-ares2_1.14.0-1ubuntu0.1_amd64.deb ...\n",
      "Unpacking libc-ares2:amd64 (1.14.0-1ubuntu0.1) ...\n",
      "Selecting previously unselected package aria2.\n",
      "Preparing to unpack .../aria2_1.33.1-1_amd64.deb ...\n",
      "Unpacking aria2 (1.33.1-1) ...\n",
      "Setting up libc-ares2:amd64 (1.14.0-1ubuntu0.1) ...\n",
      "Setting up aria2 (1.33.1-1) ...\n",
      "Processing triggers for man-db (2.8.3-2ubuntu0.1) ...\n",
      "Processing triggers for libc-bin (2.27-3ubuntu1.3) ...\n",
      "/sbin/ldconfig.real: /usr/local/lib/python3.7/dist-packages/ideep4py/lib/libmkldnn.so.0 is not a symbolic link\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# !pip install biopython biotite\n",
    "# !pip install git+https://github.com/facebookresearch/esm.git\n",
    "# !apt-get install aria2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "O0_SqulVQ9Kh"
   },
   "source": [
    "### Download Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "pp3DicGHSAI4",
    "outputId": "57f0ebc0-08fe-484f-82c4-3c920c71346b"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
      "                                 Dload  Upload   Total   Spent    Left  Speed\n",
      "100  508k    0  508k    0     0  2689k      0 --:--:-- --:--:-- --:--:-- 2689k\n",
      "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
      "                                 Dload  Upload   Total   Spent    Left  Speed\n",
      "100 1134k    0 1134k    0     0  5970k      0 --:--:-- --:--:-- --:--:-- 5970k\n",
      "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
      "                                 Dload  Upload   Total   Spent    Left  Speed\n",
      "100  547k    0  547k    0     0  3143k      0 --:--:-- --:--:-- --:--:-- 3143k\n",
      "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
      "                                 Dload  Upload   Total   Spent    Left  Speed\n",
      "100  147k  100  147k    0     0   924k      0 --:--:-- --:--:-- --:--:--  924k\n",
      "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
      "                                 Dload  Upload   Total   Spent    Left  Speed\n",
      "100  127k  100  127k    0     0   761k      0 --:--:-- --:--:-- --:--:--  757k\n",
      "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
      "                                 Dload  Upload   Total   Spent    Left  Speed\n",
      "100  181k  100  181k    0     0  1008k      0 --:--:-- --:--:-- --:--:-- 1008k\n"
     ]
    }
   ],
   "source": [
    "# # Download MSAs from esm example repo\n",
    "# !curl -O https://raw.githubusercontent.com/facebookresearch/esm/main/examples/data/1a3a_1_A.a3m\n",
    "# !curl -O https://raw.githubusercontent.com/facebookresearch/esm/main/examples/data/5ahw_1_A.a3m\n",
    "# !curl -O https://raw.githubusercontent.com/facebookresearch/esm/main/examples/data/1xcr_1_A.a3m"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Nad5sAXqREhx"
   },
   "source": [
    "### Download model weights\n",
    "This download code is technically unnecessary. ESM will download weights automatically. However, it's *really* slow on colab. aria2c is much faster."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "8e2GzK00RT_L",
    "outputId": "277db03e-2922-4cd3-c436-44bc11e0d26f"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "04/12 20:46:44 [\u001b[1;32mNOTICE\u001b[0m] Downloading 1 item(s)\n",
      "\n",
      "04/12 20:46:44 [\u001b[1;32mNOTICE\u001b[0m] GID#2bb7743048f09594 - Download has already completed: /root/.cache/torch/hub/checkpoints/esm1b_t33_650M_UR50S.pt\n",
      "\n",
      "04/12 20:46:44 [\u001b[1;32mNOTICE\u001b[0m] Download complete: /root/.cache/torch/hub/checkpoints/esm1b_t33_650M_UR50S.pt\n",
      "\n",
      "Download Results:\n",
      "gid   |stat|avg speed  |path/URI\n",
      "======+====+===========+=======================================================\n",
      "2bb774|\u001b[1;32mOK\u001b[0m  |       0B/s|/root/.cache/torch/hub/checkpoints/esm1b_t33_650M_UR50S.pt\n",
      "\n",
      "Status Legend:\n",
      "(OK):download completed.\n",
      "\n",
      "04/12 20:46:44 [\u001b[1;32mNOTICE\u001b[0m] Downloading 1 item(s)\n",
      "\n",
      "04/12 20:46:45 [\u001b[1;32mNOTICE\u001b[0m] GID#9acf7bb38fe44e13 - Download has already completed: /root/.cache/torch/hub/checkpoints/esm1b_t33_650M_UR50S-contact-regression.pt\n",
      "\n",
      "04/12 20:46:45 [\u001b[1;32mNOTICE\u001b[0m] Download complete: /root/.cache/torch/hub/checkpoints/esm1b_t33_650M_UR50S-contact-regression.pt\n",
      "\n",
      "Download Results:\n",
      "gid   |stat|avg speed  |path/URI\n",
      "======+====+===========+=======================================================\n",
      "9acf7b|\u001b[1;32mOK\u001b[0m  |       0B/s|/root/.cache/torch/hub/checkpoints/esm1b_t33_650M_UR50S-contact-regression.pt\n",
      "\n",
      "Status Legend:\n",
      "(OK):download completed.\n",
      "\n",
      "04/12 20:46:45 [\u001b[1;32mNOTICE\u001b[0m] Downloading 1 item(s)\n",
      "\u001b[0m\n",
      "04/12 20:47:00 [\u001b[1;32mNOTICE\u001b[0m] Download complete: /root/.cache/torch/hub/checkpoints/esm_msa1b_t12_100M_UR50S.pt\n",
      "\n",
      "Download Results:\n",
      "gid   |stat|avg speed  |path/URI\n",
      "======+====+===========+=======================================================\n",
      "d9b729|\u001b[1;32mOK\u001b[0m  |    88MiB/s|/root/.cache/torch/hub/checkpoints/esm_msa1b_t12_100M_UR50S.pt\n",
      "\n",
      "Status Legend:\n",
      "(OK):download completed.\n",
      "\n",
      "04/12 20:47:01 [\u001b[1;32mNOTICE\u001b[0m] Downloading 1 item(s)\n",
      "\n",
      "04/12 20:47:01 [\u001b[1;32mNOTICE\u001b[0m] Download complete: /root/.cache/torch/hub/checkpoints/esm_msa1b_t12_100M_UR50S-contact-regression.pt\n",
      "\n",
      "Download Results:\n",
      "gid   |stat|avg speed  |path/URI\n",
      "======+====+===========+=======================================================\n",
      "fb2e95|\u001b[1;32mOK\u001b[0m  |        n/a|/root/.cache/torch/hub/checkpoints/esm_msa1b_t12_100M_UR50S-contact-regression.pt\n",
      "\n",
      "Status Legend:\n",
      "(OK):download completed.\n"
     ]
    }
   ],
   "source": [
    "# !mkdir -p /root/.cache/torch/hub/checkpoints\n",
    "# !aria2c --dir=/root/.cache/torch/hub/checkpoints --continue --split 8 --max-connection-per-server 8\\\n",
    "#     https://dl.fbaipublicfiles.com/fair-esm/models/esm2_t33_650M_UR50S.pt\n",
    "# !aria2c --dir=/root/.cache/torch/hub/checkpoints --continue --split 8 --max-connection-per-server 8\\\n",
    "#     https://dl.fbaipublicfiles.com/fair-esm/regression/esm2_t33_650M_UR50S-contact-regression.pt\n",
    "# !aria2c --dir=/root/.cache/torch/hub/checkpoints --continue --split 8 --max-connection-per-server 8\\\n",
    "#     https://dl.fbaipublicfiles.com/fair-esm/models/esm_msa1b_t12_100M_UR50S.pt\n",
    "# !aria2c --dir=/root/.cache/torch/hub/checkpoints --continue --split 8 --max-connection-per-server 8\\\n",
    "#     https://dl.fbaipublicfiles.com/fair-esm/regression/esm_msa1b_t12_100M_UR50S-contact-regression.pt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "q1eZWXv1bxGl"
   },
   "source": [
    "## Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "fQ8ztOjvQbJV",
    "outputId": "44da6a25-109b-44ed-db6c-dcfdb224ee4a"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<torch.autograd.grad_mode.set_grad_enabled at 0x7f793fdc4190>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from typing import List, Tuple, Optional, Dict, NamedTuple, Union, Callable\n",
    "import itertools\n",
    "import os\n",
    "import string\n",
    "from pathlib import Path\n",
    "\n",
    "import numpy as np\n",
    "import torch\n",
    "from scipy.spatial.distance import squareform, pdist, cdist\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib as mpl\n",
    "from Bio import SeqIO\n",
    "import biotite.structure as bs\n",
    "from biotite.structure.io.pdbx import PDBxFile, get_structure\n",
    "from biotite.database import rcsb\n",
    "from tqdm import tqdm\n",
    "import pandas as pd\n",
    "\n",
    "import esm\n",
    "\n",
    "torch.set_grad_enabled(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "i7iXPaDKZ5vx"
   },
   "source": [
    "## Define Functions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "rb4cDoG2ns91"
   },
   "source": [
    "### Parsing alignments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "id": "Lpt-Ijz2T6zF"
   },
   "outputs": [],
   "source": [
    "# This is an efficient way to delete lowercase characters and insertion characters from a string\n",
    "deletekeys = dict.fromkeys(string.ascii_lowercase)\n",
    "deletekeys[\".\"] = None\n",
    "deletekeys[\"*\"] = None\n",
    "translation = str.maketrans(deletekeys)\n",
    "\n",
    "def read_sequence(filename: str) -> Tuple[str, str]:\n",
    "    \"\"\" Reads the first (reference) sequences from a fasta or MSA file.\"\"\"\n",
    "    record = next(SeqIO.parse(filename, \"fasta\"))\n",
    "    return record.description, str(record.seq)\n",
    "\n",
    "def remove_insertions(sequence: str) -> str:\n",
    "    \"\"\" Removes any insertions into the sequence. Needed to load aligned sequences in an MSA. \"\"\"\n",
    "    return sequence.translate(translation)\n",
    "\n",
    "def read_msa(filename: str) -> List[Tuple[str, str]]:\n",
    "    \"\"\" Reads the sequences from an MSA file, automatically removes insertions.\"\"\"\n",
    "    return [(record.description, remove_insertions(str(record.seq))) for record in SeqIO.parse(filename, \"fasta\")]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "tV3WCbn6aXL7"
   },
   "source": [
    "### Converting structures to contacts\n",
    "\n",
    "There are many ways to define a protein contact. Here we're using the definition of 8 angstroms between carbon beta atoms. Note that the position of the carbon beta is imputed from the position of the N, CA, and C atoms for each residue."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "id": "n4FBkOUaWuXb"
   },
   "outputs": [],
   "source": [
    "def extend(a, b, c, L, A, D):\n",
    "    \"\"\"\n",
    "    input:  3 coords (a,b,c), (L)ength, (A)ngle, and (D)ihedral\n",
    "    output: 4th coord\n",
    "    \"\"\"\n",
    "\n",
    "    def normalize(x):\n",
    "        return x / np.linalg.norm(x, ord=2, axis=-1, keepdims=True)\n",
    "\n",
    "    bc = normalize(b - c)\n",
    "    n = normalize(np.cross(b - a, bc))\n",
    "    m = [bc, np.cross(n, bc), n]\n",
    "    d = [L * np.cos(A), L * np.sin(A) * np.cos(D), -L * np.sin(A) * np.sin(D)]\n",
    "    return c + sum([m * d for m, d in zip(m, d)])\n",
    "\n",
    "\n",
    "def contacts_from_pdb(\n",
    "    structure: bs.AtomArray,\n",
    "    distance_threshold: float = 8.0,\n",
    "    chain: Optional[str] = None,\n",
    ") -> np.ndarray:\n",
    "    mask = ~structure.hetero\n",
    "    if chain is not None:\n",
    "        mask &= structure.chain_id == chain\n",
    "\n",
    "    N = structure.coord[mask & (structure.atom_name == \"N\")]\n",
    "    CA = structure.coord[mask & (structure.atom_name == \"CA\")]\n",
    "    C = structure.coord[mask & (structure.atom_name == \"C\")]\n",
    "\n",
    "    Cbeta = extend(C, N, CA, 1.522, 1.927, -2.143)\n",
    "    dist = squareform(pdist(Cbeta))\n",
    "    \n",
    "    contacts = dist < distance_threshold\n",
    "    contacts = contacts.astype(np.int64)\n",
    "    contacts[np.isnan(dist)] = -1\n",
    "    return contacts"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "mqwybh2Tn_Ou"
   },
   "source": [
    "### Subsampling MSA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "id": "dSdxag5OmOmK"
   },
   "outputs": [],
   "source": [
    "# Select sequences from the MSA to maximize the hamming distance\n",
    "# Alternatively, can use hhfilter \n",
    "def greedy_select(msa: List[Tuple[str, str]], num_seqs: int, mode: str = \"max\") -> List[Tuple[str, str]]:\n",
    "    assert mode in (\"max\", \"min\")\n",
    "    if len(msa) <= num_seqs:\n",
    "        return msa\n",
    "    \n",
    "    array = np.array([list(seq) for _, seq in msa], dtype=np.bytes_).view(np.uint8)\n",
    "\n",
    "    optfunc = np.argmax if mode == \"max\" else np.argmin\n",
    "    all_indices = np.arange(len(msa))\n",
    "    indices = [0]\n",
    "    pairwise_distances = np.zeros((0, len(msa)))\n",
    "    for _ in range(num_seqs - 1):\n",
    "        dist = cdist(array[indices[-1:]], array, \"hamming\")\n",
    "        pairwise_distances = np.concatenate([pairwise_distances, dist])\n",
    "        shifted_distance = np.delete(pairwise_distances, indices, axis=1).mean(0)\n",
    "        shifted_index = optfunc(shifted_distance)\n",
    "        index = np.delete(all_indices, indices)[shifted_index]\n",
    "        indices.append(index)\n",
    "    indices = sorted(indices)\n",
    "    return [msa[idx] for idx in indices]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "lW5thQpSn0Rp"
   },
   "source": [
    "### Compute contact precisions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "id": "c7T9xWTXeIaR"
   },
   "outputs": [],
   "source": [
    "def compute_precisions(\n",
    "    predictions: torch.Tensor,\n",
    "    targets: torch.Tensor,\n",
    "    src_lengths: Optional[torch.Tensor] = None,\n",
    "    minsep: int = 6,\n",
    "    maxsep: Optional[int] = None,\n",
    "    override_length: Optional[int] = None,  # for casp\n",
    "):\n",
    "    if isinstance(predictions, np.ndarray):\n",
    "        predictions = torch.from_numpy(predictions)\n",
    "    if isinstance(targets, np.ndarray):\n",
    "        targets = torch.from_numpy(targets)\n",
    "    if predictions.dim() == 2:\n",
    "        predictions = predictions.unsqueeze(0)\n",
    "    if targets.dim() == 2:\n",
    "        targets = targets.unsqueeze(0)\n",
    "    override_length = (targets[0, 0] >= 0).sum()\n",
    "\n",
    "    # Check sizes\n",
    "    if predictions.size() != targets.size():\n",
    "        raise ValueError(\n",
    "            f\"Size mismatch. Received predictions of size {predictions.size()}, \"\n",
    "            f\"targets of size {targets.size()}\"\n",
    "        )\n",
    "    device = predictions.device\n",
    "\n",
    "    batch_size, seqlen, _ = predictions.size()\n",
    "    seqlen_range = torch.arange(seqlen, device=device)\n",
    "\n",
    "    sep = seqlen_range.unsqueeze(0) - seqlen_range.unsqueeze(1)\n",
    "    sep = sep.unsqueeze(0)\n",
    "    valid_mask = sep >= minsep\n",
    "    valid_mask = valid_mask & (targets >= 0)  # negative targets are invalid\n",
    "\n",
    "    if maxsep is not None:\n",
    "        valid_mask &= sep < maxsep\n",
    "\n",
    "    if src_lengths is not None:\n",
    "        valid = seqlen_range.unsqueeze(0) < src_lengths.unsqueeze(1)\n",
    "        valid_mask &= valid.unsqueeze(1) & valid.unsqueeze(2)\n",
    "    else:\n",
    "        src_lengths = torch.full([batch_size], seqlen, device=device, dtype=torch.long)\n",
    "\n",
    "    predictions = predictions.masked_fill(~valid_mask, float(\"-inf\"))\n",
    "\n",
    "    x_ind, y_ind = np.triu_indices(seqlen, minsep)\n",
    "    predictions_upper = predictions[:, x_ind, y_ind]\n",
    "    targets_upper = targets[:, x_ind, y_ind]\n",
    "\n",
    "    topk = seqlen if override_length is None else max(seqlen, override_length)\n",
    "    indices = predictions_upper.argsort(dim=-1, descending=True)[:, :topk]\n",
    "    topk_targets = targets_upper[torch.arange(batch_size).unsqueeze(1), indices]\n",
    "    if topk_targets.size(1) < topk:\n",
    "        topk_targets = F.pad(topk_targets, [0, topk - topk_targets.size(1)])\n",
    "\n",
    "    cumulative_dist = topk_targets.type_as(predictions).cumsum(-1)\n",
    "\n",
    "    gather_lengths = src_lengths.unsqueeze(1)\n",
    "    if override_length is not None:\n",
    "        gather_lengths = override_length * torch.ones_like(\n",
    "            gather_lengths, device=device\n",
    "        )\n",
    "\n",
    "    gather_indices = (\n",
    "        torch.arange(0.1, 1.1, 0.1, device=device).unsqueeze(0) * gather_lengths\n",
    "    ).type(torch.long) - 1\n",
    "\n",
    "    binned_cumulative_dist = cumulative_dist.gather(1, gather_indices)\n",
    "    binned_precisions = binned_cumulative_dist / (gather_indices + 1).type_as(\n",
    "        binned_cumulative_dist\n",
    "    )\n",
    "\n",
    "    pl5 = binned_precisions[:, 1]\n",
    "    pl2 = binned_precisions[:, 4]\n",
    "    pl = binned_precisions[:, 9]\n",
    "    auc = binned_precisions.mean(-1)\n",
    "\n",
    "    return {\"AUC\": auc, \"P@L\": pl, \"P@L2\": pl2, \"P@L5\": pl5}\n",
    "\n",
    "\n",
    "def evaluate_prediction(\n",
    "    predictions: torch.Tensor,\n",
    "    targets: torch.Tensor,\n",
    ") -> Dict[str, float]:\n",
    "    if isinstance(targets, np.ndarray):\n",
    "        targets = torch.from_numpy(targets)\n",
    "    contact_ranges = [\n",
    "        (\"local\", 3, 6),\n",
    "        (\"short\", 6, 12),\n",
    "        (\"medium\", 12, 24),\n",
    "        (\"long\", 24, None),\n",
    "    ]\n",
    "    metrics = {}\n",
    "    targets = targets.to(predictions.device)\n",
    "    for name, minsep, maxsep in contact_ranges:\n",
    "        rangemetrics = compute_precisions(\n",
    "            predictions,\n",
    "            targets,\n",
    "            minsep=minsep,\n",
    "            maxsep=maxsep,\n",
    "        )\n",
    "        for key, val in rangemetrics.items():\n",
    "            metrics[f\"{name}_{key}\"] = val.item()\n",
    "    return metrics"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "cvYiSUg7n5rP"
   },
   "source": [
    "### Plotting Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "id": "pG3gTskUfyfy"
   },
   "outputs": [],
   "source": [
    "\"\"\"Adapted from: https://github.com/rmrao/evo/blob/main/evo/visualize.py\"\"\"\n",
    "def plot_contacts_and_predictions(\n",
    "    predictions: Union[torch.Tensor, np.ndarray],\n",
    "    contacts: Union[torch.Tensor, np.ndarray],\n",
    "    ax: Optional[mpl.axes.Axes] = None,\n",
    "    # artists: Optional[ContactAndPredictionArtists] = None,\n",
    "    cmap: str = \"Blues\",\n",
    "    ms: float = 1,\n",
    "    title: Union[bool, str, Callable[[float], str]] = True,\n",
    "    animated: bool = False,\n",
    ") -> None:\n",
    "\n",
    "    if isinstance(predictions, torch.Tensor):\n",
    "        predictions = predictions.detach().cpu().numpy()\n",
    "    if isinstance(contacts, torch.Tensor):\n",
    "        contacts = contacts.detach().cpu().numpy()\n",
    "    if ax is None:\n",
    "        ax = plt.gca()\n",
    "\n",
    "    seqlen = contacts.shape[0]\n",
    "    relative_distance = np.add.outer(-np.arange(seqlen), np.arange(seqlen))\n",
    "    bottom_mask = relative_distance < 0\n",
    "    masked_image = np.ma.masked_where(bottom_mask, predictions)\n",
    "    invalid_mask = np.abs(np.add.outer(np.arange(seqlen), -np.arange(seqlen))) < 6\n",
    "    predictions = predictions.copy()\n",
    "    predictions[invalid_mask] = float(\"-inf\")\n",
    "\n",
    "    topl_val = np.sort(predictions.reshape(-1))[-seqlen]\n",
    "    pred_contacts = predictions >= topl_val\n",
    "    true_positives = contacts & pred_contacts & ~bottom_mask\n",
    "    false_positives = ~contacts & pred_contacts & ~bottom_mask\n",
    "    other_contacts = contacts & ~pred_contacts & ~bottom_mask\n",
    "\n",
    "    if isinstance(title, str):\n",
    "        title_text: Optional[str] = title\n",
    "    elif title:\n",
    "        long_range_pl = compute_precisions(predictions, contacts, minsep=24)[\n",
    "            \"P@L\"\n",
    "        ].item()\n",
    "        if callable(title):\n",
    "            title_text = title(long_range_pl)\n",
    "        else:\n",
    "            title_text = f\"Long Range P@L: {100 * long_range_pl:0.1f}\"\n",
    "    else:\n",
    "        title_text = None\n",
    "\n",
    "    img = ax.imshow(masked_image, cmap=cmap, animated=animated)\n",
    "    oc = ax.plot(*np.where(other_contacts), \"o\", c=\"grey\", ms=ms)[0]\n",
    "    fn = ax.plot(*np.where(false_positives), \"o\", c=\"r\", ms=ms)[0]\n",
    "    tp = ax.plot(*np.where(true_positives), \"o\", c=\"b\", ms=ms)[0]\n",
    "    ti = ax.set_title(title_text) if title_text is not None else None\n",
    "    # artists = ContactAndPredictionArtists(img, oc, fn, tp, ti)\n",
    "\n",
    "    ax.axis(\"square\")\n",
    "    ax.set_xlim([0, seqlen])\n",
    "    ax.set_ylim([0, seqlen])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "6T7Pcz-poDFn"
   },
   "source": [
    "## Predict and Visualize"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "WnZSlf1EoGys"
   },
   "source": [
    "### Read Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "id": "FS8xLDd9ZJfN"
   },
   "outputs": [],
   "source": [
    "# This is where the data is actually read in\n",
    "PDB_IDS = [\"1a3a\", \"5ahw\", \"1xcr\"]\n",
    "\n",
    "structures = {\n",
    "    name.lower(): get_structure(PDBxFile.read(rcsb.fetch(name, \"cif\")))[0]\n",
    "    for name in PDB_IDS\n",
    "}\n",
    "\n",
    "contacts = {\n",
    "    name: contacts_from_pdb(structure, chain=\"A\") \n",
    "    for name, structure in structures.items()\n",
    "}\n",
    "\n",
    "msas = {\n",
    "    name: read_msa(f\"data/{name.lower()}_1_A.a3m\")\n",
    "    for name in PDB_IDS\n",
    "}\n",
    "\n",
    "sequences = {\n",
    "    name: msa[0] for name, msa in msas.items()\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "jacL9LZXoJYD"
   },
   "source": [
    "### ESM-2 Predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "id": "Kwh2szcbYvKm"
   },
   "outputs": [],
   "source": [
    "esm2, esm2_alphabet = esm.pretrained.esm2_t33_650M_UR50D()\n",
    "esm2 = esm2.eval().cuda()\n",
    "esm2_batch_converter = esm2_alphabet.get_batch_converter()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 259
    },
    "id": "Qce87TjvbEDA",
    "outputId": "1b2415cb-ec14-4163-9466-b621e1d29885"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>model</th>\n",
       "      <th>local_AUC</th>\n",
       "      <th>local_P@L</th>\n",
       "      <th>local_P@L2</th>\n",
       "      <th>local_P@L5</th>\n",
       "      <th>short_AUC</th>\n",
       "      <th>short_P@L</th>\n",
       "      <th>short_P@L2</th>\n",
       "      <th>short_P@L5</th>\n",
       "      <th>medium_AUC</th>\n",
       "      <th>medium_P@L</th>\n",
       "      <th>medium_P@L2</th>\n",
       "      <th>medium_P@L5</th>\n",
       "      <th>long_AUC</th>\n",
       "      <th>long_P@L</th>\n",
       "      <th>long_P@L2</th>\n",
       "      <th>long_P@L5</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1a3a</td>\n",
       "      <td>ESM-2 (Unsupervised)</td>\n",
       "      <td>0.801181</td>\n",
       "      <td>0.662069</td>\n",
       "      <td>0.805556</td>\n",
       "      <td>0.896552</td>\n",
       "      <td>0.528245</td>\n",
       "      <td>0.296552</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.827586</td>\n",
       "      <td>0.612222</td>\n",
       "      <td>0.344828</td>\n",
       "      <td>0.569444</td>\n",
       "      <td>0.931035</td>\n",
       "      <td>0.806507</td>\n",
       "      <td>0.689655</td>\n",
       "      <td>0.791667</td>\n",
       "      <td>0.931035</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5ahw</td>\n",
       "      <td>ESM-2 (Unsupervised)</td>\n",
       "      <td>0.819763</td>\n",
       "      <td>0.680000</td>\n",
       "      <td>0.838710</td>\n",
       "      <td>0.960000</td>\n",
       "      <td>0.543314</td>\n",
       "      <td>0.296000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.840000</td>\n",
       "      <td>0.569258</td>\n",
       "      <td>0.304000</td>\n",
       "      <td>0.548387</td>\n",
       "      <td>0.920000</td>\n",
       "      <td>0.937361</td>\n",
       "      <td>0.864000</td>\n",
       "      <td>0.951613</td>\n",
       "      <td>0.960000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1xcr</td>\n",
       "      <td>ESM-2 (Unsupervised)</td>\n",
       "      <td>0.529522</td>\n",
       "      <td>0.351438</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.693548</td>\n",
       "      <td>0.344734</td>\n",
       "      <td>0.204473</td>\n",
       "      <td>0.320513</td>\n",
       "      <td>0.516129</td>\n",
       "      <td>0.410161</td>\n",
       "      <td>0.265176</td>\n",
       "      <td>0.365385</td>\n",
       "      <td>0.596774</td>\n",
       "      <td>0.576668</td>\n",
       "      <td>0.408946</td>\n",
       "      <td>0.544872</td>\n",
       "      <td>0.758065</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     id                 model  local_AUC  local_P@L  local_P@L2  local_P@L5  \\\n",
       "0  1a3a  ESM-2 (Unsupervised)   0.801181   0.662069    0.805556    0.896552   \n",
       "1  5ahw  ESM-2 (Unsupervised)   0.819763   0.680000    0.838710    0.960000   \n",
       "2  1xcr  ESM-2 (Unsupervised)   0.529522   0.351438    0.500000    0.693548   \n",
       "\n",
       "   short_AUC  short_P@L  short_P@L2  short_P@L5  medium_AUC  medium_P@L  \\\n",
       "0   0.528245   0.296552    0.500000    0.827586    0.612222    0.344828   \n",
       "1   0.543314   0.296000    0.500000    0.840000    0.569258    0.304000   \n",
       "2   0.344734   0.204473    0.320513    0.516129    0.410161    0.265176   \n",
       "\n",
       "   medium_P@L2  medium_P@L5  long_AUC  long_P@L  long_P@L2  long_P@L5  \n",
       "0     0.569444     0.931035  0.806507  0.689655   0.791667   0.931035  \n",
       "1     0.548387     0.920000  0.937361  0.864000   0.951613   0.960000  \n",
       "2     0.365385     0.596774  0.576668  0.408946   0.544872   0.758065  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "esm2_predictions = {}\n",
    "esm2_results = []\n",
    "for name, inputs in sequences.items():\n",
    "    esm2_batch_labels, esm2_batch_strs, esm2_batch_tokens = esm2_batch_converter([inputs])\n",
    "    esm2_batch_tokens = esm2_batch_tokens.to(next(esm2.parameters()).device)\n",
    "    esm2_predictions[name] = esm2.predict_contacts(esm2_batch_tokens)[0].cpu()\n",
    "    metrics = {\"id\": name, \"model\": \"ESM-2 (Unsupervised)\"}\n",
    "    metrics.update(evaluate_prediction(esm2_predictions[name], contacts[name]))\n",
    "    esm2_results.append(metrics)\n",
    "esm2_results = pd.DataFrame(esm2_results)\n",
    "display(esm2_results)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 359
    },
    "id": "WnlwYZeUbgLO",
    "outputId": "74a540b3-7042-4028-a122-ef79b589321f"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x432 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(figsize=(18, 6), ncols=3)\n",
    "for ax, name in zip(axes, PDB_IDS):\n",
    "    prediction = esm2_predictions[name]\n",
    "    target = contacts[name]\n",
    "    plot_contacts_and_predictions(\n",
    "        prediction, target, ax=ax, title = lambda prec: f\"{name}: Long Range P@L: {100 * prec:0.1f}\"\n",
    "    )\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "IohE_rsToQAK"
   },
   "source": [
    "### MSA Transformer Predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "kIiH7a5olI_A"
   },
   "outputs": [],
   "source": [
    "msa_transformer, msa_transformer_alphabet = esm.pretrained.esm_msa1b_t12_100M_UR50S()\n",
    "msa_transformer = msa_transformer.eval().cuda()\n",
    "msa_transformer_batch_converter = msa_transformer_alphabet.get_batch_converter()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 311
    },
    "id": "p7USWOF2lWwJ",
    "outputId": "972f74cb-7b67-4a73-9d7c-f593b097c1a5"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "  <div id=\"df-8cefe40d-0b87-4eda-886d-404f729e0636\">\n",
       "    <div class=\"colab-df-container\">\n",
       "      <div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>model</th>\n",
       "      <th>local_AUC</th>\n",
       "      <th>local_P@L</th>\n",
       "      <th>local_P@L2</th>\n",
       "      <th>local_P@L5</th>\n",
       "      <th>short_AUC</th>\n",
       "      <th>short_P@L</th>\n",
       "      <th>short_P@L2</th>\n",
       "      <th>short_P@L5</th>\n",
       "      <th>medium_AUC</th>\n",
       "      <th>medium_P@L</th>\n",
       "      <th>medium_P@L2</th>\n",
       "      <th>medium_P@L5</th>\n",
       "      <th>long_AUC</th>\n",
       "      <th>long_P@L</th>\n",
       "      <th>long_P@L2</th>\n",
       "      <th>long_P@L5</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1a3a</td>\n",
       "      <td>MSA Transformer (Unsupervised)</td>\n",
       "      <td>0.853126</td>\n",
       "      <td>0.765517</td>\n",
       "      <td>0.875000</td>\n",
       "      <td>0.827586</td>\n",
       "      <td>0.575057</td>\n",
       "      <td>0.317241</td>\n",
       "      <td>0.569444</td>\n",
       "      <td>0.862069</td>\n",
       "      <td>0.601065</td>\n",
       "      <td>0.337931</td>\n",
       "      <td>0.597222</td>\n",
       "      <td>0.827586</td>\n",
       "      <td>0.837919</td>\n",
       "      <td>0.724138</td>\n",
       "      <td>0.861111</td>\n",
       "      <td>0.896552</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5ahw</td>\n",
       "      <td>MSA Transformer (Unsupervised)</td>\n",
       "      <td>0.850377</td>\n",
       "      <td>0.736000</td>\n",
       "      <td>0.854839</td>\n",
       "      <td>0.920000</td>\n",
       "      <td>0.547282</td>\n",
       "      <td>0.288000</td>\n",
       "      <td>0.548387</td>\n",
       "      <td>0.880000</td>\n",
       "      <td>0.581426</td>\n",
       "      <td>0.320000</td>\n",
       "      <td>0.548387</td>\n",
       "      <td>0.880000</td>\n",
       "      <td>0.967116</td>\n",
       "      <td>0.896000</td>\n",
       "      <td>0.967742</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1xcr</td>\n",
       "      <td>MSA Transformer (Unsupervised)</td>\n",
       "      <td>0.675652</td>\n",
       "      <td>0.469649</td>\n",
       "      <td>0.679487</td>\n",
       "      <td>0.870968</td>\n",
       "      <td>0.470373</td>\n",
       "      <td>0.249201</td>\n",
       "      <td>0.442308</td>\n",
       "      <td>0.709677</td>\n",
       "      <td>0.508027</td>\n",
       "      <td>0.316294</td>\n",
       "      <td>0.487179</td>\n",
       "      <td>0.677419</td>\n",
       "      <td>0.878467</td>\n",
       "      <td>0.769968</td>\n",
       "      <td>0.891026</td>\n",
       "      <td>0.967742</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>\n",
       "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-8cefe40d-0b87-4eda-886d-404f729e0636')\"\n",
       "              title=\"Convert this dataframe to an interactive table.\"\n",
       "              style=\"display:none;\">\n",
       "        \n",
       "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
       "       width=\"24px\">\n",
       "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
       "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
       "  </svg>\n",
       "      </button>\n",
       "      \n",
       "  <style>\n",
       "    .colab-df-container {\n",
       "      display:flex;\n",
       "      flex-wrap:wrap;\n",
       "      gap: 12px;\n",
       "    }\n",
       "\n",
       "    .colab-df-convert {\n",
       "      background-color: #E8F0FE;\n",
       "      border: none;\n",
       "      border-radius: 50%;\n",
       "      cursor: pointer;\n",
       "      display: none;\n",
       "      fill: #1967D2;\n",
       "      height: 32px;\n",
       "      padding: 0 0 0 0;\n",
       "      width: 32px;\n",
       "    }\n",
       "\n",
       "    .colab-df-convert:hover {\n",
       "      background-color: #E2EBFA;\n",
       "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
       "      fill: #174EA6;\n",
       "    }\n",
       "\n",
       "    [theme=dark] .colab-df-convert {\n",
       "      background-color: #3B4455;\n",
       "      fill: #D2E3FC;\n",
       "    }\n",
       "\n",
       "    [theme=dark] .colab-df-convert:hover {\n",
       "      background-color: #434B5C;\n",
       "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
       "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
       "      fill: #FFFFFF;\n",
       "    }\n",
       "  </style>\n",
       "\n",
       "      <script>\n",
       "        const buttonEl =\n",
       "          document.querySelector('#df-8cefe40d-0b87-4eda-886d-404f729e0636 button.colab-df-convert');\n",
       "        buttonEl.style.display =\n",
       "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
       "\n",
       "        async function convertToInteractive(key) {\n",
       "          const element = document.querySelector('#df-8cefe40d-0b87-4eda-886d-404f729e0636');\n",
       "          const dataTable =\n",
       "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
       "                                                     [key], {});\n",
       "          if (!dataTable) return;\n",
       "\n",
       "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
       "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
       "            + ' to learn more about interactive tables.';\n",
       "          element.innerHTML = '';\n",
       "          dataTable['output_type'] = 'display_data';\n",
       "          await google.colab.output.renderOutput(dataTable, element);\n",
       "          const docLink = document.createElement('div');\n",
       "          docLink.innerHTML = docLinkHtml;\n",
       "          element.appendChild(docLink);\n",
       "        }\n",
       "      </script>\n",
       "    </div>\n",
       "  </div>\n",
       "  "
      ],
      "text/plain": [
       "     id                           model  local_AUC  local_P@L  local_P@L2  \\\n",
       "0  1a3a  MSA Transformer (Unsupervised)   0.853126   0.765517    0.875000   \n",
       "1  5ahw  MSA Transformer (Unsupervised)   0.850377   0.736000    0.854839   \n",
       "2  1xcr  MSA Transformer (Unsupervised)   0.675652   0.469649    0.679487   \n",
       "\n",
       "   local_P@L5  short_AUC  short_P@L  short_P@L2  short_P@L5  medium_AUC  \\\n",
       "0    0.827586   0.575057   0.317241    0.569444    0.862069    0.601065   \n",
       "1    0.920000   0.547282   0.288000    0.548387    0.880000    0.581426   \n",
       "2    0.870968   0.470373   0.249201    0.442308    0.709677    0.508027   \n",
       "\n",
       "   medium_P@L  medium_P@L2  medium_P@L5  long_AUC  long_P@L  long_P@L2  \\\n",
       "0    0.337931     0.597222     0.827586  0.837919  0.724138   0.861111   \n",
       "1    0.320000     0.548387     0.880000  0.967116  0.896000   0.967742   \n",
       "2    0.316294     0.487179     0.677419  0.878467  0.769968   0.891026   \n",
       "\n",
       "   long_P@L5  \n",
       "0   0.896552  \n",
       "1   1.000000  \n",
       "2   0.967742  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "msa_transformer_predictions = {}\n",
    "msa_transformer_results = []\n",
    "for name, inputs in msas.items():\n",
    "    inputs = greedy_select(inputs, num_seqs=128) # can change this to pass more/fewer sequences\n",
    "    msa_transformer_batch_labels, msa_transformer_batch_strs, msa_transformer_batch_tokens = msa_transformer_batch_converter([inputs])\n",
    "    msa_transformer_batch_tokens = msa_transformer_batch_tokens.to(next(msa_transformer.parameters()).device)\n",
    "    msa_transformer_predictions[name] = msa_transformer.predict_contacts(msa_transformer_batch_tokens)[0].cpu()\n",
    "    metrics = {\"id\": name, \"model\": \"MSA Transformer (Unsupervised)\"}\n",
    "    metrics.update(evaluate_prediction(msa_transformer_predictions[name], contacts[name]))\n",
    "    msa_transformer_results.append(metrics)\n",
    "msa_transformer_results = pd.DataFrame(msa_transformer_results)\n",
    "display(msa_transformer_results)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 359
    },
    "id": "6iPBer65nPRI",
    "outputId": "10f21020-80a7-4a87-9343-2cb6df0a3890"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x432 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(figsize=(18, 6), ncols=3)\n",
    "for ax, name in zip(axes, PDB_IDS):\n",
    "    prediction = msa_transformer_predictions[name]\n",
    "    target = contacts[name]\n",
    "    plot_contacts_and_predictions(\n",
    "        prediction, target, ax=ax, title = lambda prec: f\"{name}: Long Range P@L: {100 * prec:0.1f}\"\n",
    "    )\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "accelerator": "GPU",
  "colab": {
   "collapsed_sections": [
    "U0ukYqqzateL",
    "q1eZWXv1bxGl",
    "i7iXPaDKZ5vx",
    "rb4cDoG2ns91",
    "tV3WCbn6aXL7",
    "mqwybh2Tn_Ou",
    "lW5thQpSn0Rp",
    "cvYiSUg7n5rP",
    "WnZSlf1EoGys"
   ],
   "name": "esm_contact_prediction.ipynb",
   "provenance": [],
   "toc_visible": true
  },
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
